Utility mapping and data distribution system and method

ABSTRACT

A system and method of mapping underground utilities and other subsurface objects involves one or more of acquiring utility location data using a number of different detectors and sensors, processing the multiple detector/sensor output data to produce mapping data, storing the mapping data in a database, and providing access to and use of the stored mapping data by subscribing users on a usage fee basis.

RELATED APPLICATIONS

[0001] This application claims priority to provisional application U.S.Serial No. 60/211,431, filed Jun. 14, 2000.

FIELD OF THE INVENTION

[0002] The present invention relates generally to the field ofunderground utility and object detection, and, more particularly, to oneor more of detecting buried utility and subsurface objects, mapping suchutilities and objects, and electronically distributing mapping data tosubscribing users.

BACKGROUND OF THE INVENTION

[0003] Various techniques have been developed to locate and mapunderground utilities and other manmade subsurface structures. Presentutility mapping practices take two basic forms: active systems that musthave some type of connection to the utility at some accessible pointalong its path, and passive systems that attempt to map utilitiesindependent of any connection or even prior knowledge of theirexistence.

[0004] Active systems are problematic for various reasons, such as thedifficulty and cost of physically accessing the utility and difficultyin sensing non-conductive utilities. Passive systems currently in useoften employ GPR. GPR surveys are conducted from the surface, and thelocation and relative depth to potential utilities are determined froman analysis of reflected energy.

[0005] GPR, in general, is a very good sensor for utility mappingpurposes, in that GPR is easy to use and provides excellent resolution.However, GPR has problems detecting utilities in certain soil types andconditions that limit GPR's use in many areas of the United States andthe world, such as much of southwest United States (e.g., Arizona).Improvements in GPR sensor design can help overcome some aspects ofthese inherent limitations, but in many geographic areas, GPR should notbe solely relied on due to imaging reliability and accuracy concerns.

[0006] Before trenching, boring, or otherwise engaging in invasivesubsurface activity to install or access utilities, it is imperative toknow the location of any existing utilities and/or obstructions in orderto assist in trenching or boring operations and minimize safety risks.Currently, utilities that are installed or otherwise discovered duringinstallation may have their corresponding physical locations manuallyrecorded in order to facilitate future installations. One such system isreferred to as the One-Call system, where an inquiry call can be made toobtain utility location information from an organization that manuallyrecords utility location information, when and if it is provided.However, the One-Call system is not particularly reliable, as only acertain percentage of the utilities are recorded, and those that arerecorded may have suspect or imprecise location data. As such,currently-existing location data for buried utilities is incomplete andoften questionable in terms of reliability.

[0007] There is a need in the utility installation and locatingindustries to increase the accuracy of buried utility/object detection.There exits a further need to collect, maintain, and disseminate utilitylocation data of increased accuracy. The present invention fulfillsthese and other needs, and provides additional advantages over the priorart.

SUMMARY OF THE INVENTION

[0008] The present invention is directed to improved systems and methodsof detecting underground utilities and other subsurface objects. Thepresent invention is also directed to systems and methods of mappingunderground utilities. Embodiments of the present invention are alsodirected to systems and methods of acquiring and storing mapping data ina database. Embodiments of the present invention are further directed tosystems and methods of providing access to and use of stored mappingdata by subscribing users. These and other features disclosed andclaimed herein may be employed individually or in various combinationsin accordance with the principles of the present invention.

[0009] In one embodiment, a method of detecting one or more undergroundutilities involves concurrently sensing a number of physical parametersof a subsurface, storing data associated with the sensed physicalparameters, and detecting the utilities within the subsurface using thestored data. Detecting the utilities may involve associating stored datafor each of the sensed physical parameters in terms of depth andposition.

[0010] Detecting the utilities may also involve combining the storeddata to produce combined data, and detecting the utilities within thesubsurface using the combined data. The stored data may be combined toproduce combined data expressed in terms of subsurface depth. The storeddata may also be combined to produce combined data expressed in terms ofhorizontal path length. Also, the stored data may be combined based onsoil characteristics to produce combined data. The utilities within thesubsurface can be detected using one or more of these combined datatypes.

[0011] Detecting one or more underground utilities may also involvedetermining one or more soil characteristics using one or more of thesensed physical parameters. For example, one or more of soilresistivity, conductivity, permittivity, temperature, water saturation,composition, and hardness may be determined using one or more of thesensed physical parameters.

[0012] Detecting underground utilities may involve weighting the storeddata based on signal noise associated with the sensed physicalparameters, The utilities within the subsurface can be detected usingthe weighted stored data. Detecting the utilities may further involvefusing the stored data to produce fused data. The utilities within thesubsurface can be detected using the fused data.

[0013] Tolerance factor data associated with the stored data may furtherbe computed. The tolerance factor data may be computed dynamically orsubsequent to storing the data. Weighting the stored data may beaccomplished using the tolerance factor data. Tolerance factor data maybe computed for each data point of the stored data. Tolerance factordata may also be computed for each of the detected utilities in toto.Ground truth data may be processed to enhance the accuracy of theutility detection result.

[0014] Detecting underground utilities may further involve generating amap of the detected utilities. Data associated with the map may beincorporated within a Geographic Information System or other geographicreference system. A 2-D map or a 3-D map of the detected utilities canbe generated. Data associated with one or more of the sensed physicalparameters or one or more of the detected utilities may be displayed,such as by use of an operator interface.

[0015] According to another embodiment of the present invention,detecting one or more underground utilities involves generating radarwaves and seismic waves of about the same wavelength. A number ofphysical parameters of a subsurface are concurrently sensed using theradar waves and seismic waves. Data associated with the sensed physicalparameters are stored, and the utilities within the subsurface aredetected using the stored data.

[0016] The seismic waves, in one embodiment, comprise seismic shearwaves. In one embodiment, the seismic shear waves have frequencies ofless than 1,000 Hz. In another embodiment, the seismic shear waves havefrequencies in excess of 1,000 Hz. For example, the seismic shear wavesmay have frequencies in the range of about 2,000 Hz to about 3,200 Hz.In another approach, the seismic shear waves may have frequencies of atleast about 3 kHz.

[0017] The radar waves and seismic waves typically have wavelengths fordetecting underground utilities of a predefined size. By way ofnon-limiting example, the radar waves and seismic waves may havewavelengths for detecting underground utilities having a dimension of atleast ⅜-inch. The radar waves and seismic waves may, for example, havewavelengths of about 3 inches. In general, the radar waves and seismicwaves preferably have wavelengths that can facilitate detection ofunderground utilities at depths of up to about 50 feet, preferably byuse of both wave types, but at least by use of one of the waves typesfor deeper target utilities. For example, the radar waves and seismicwaves may have wavelengths of less than about 0.5 feet for conductingnear surface (e.g., 15-30 feet or less) underground utility detection.It is understood that the principles of the present invention may beapplied for detection of utilities at depths in excess of 50 feetdepending on the detection capabilities of the detectors employed. Thedetection methodology may further involve determining velocities of theradar waves and seismic waves, respectively.

[0018] In accordance with a further embodiment of the present invention,detecting one or more underground utilities involves concurrentlysensing a number of physical parameters of a subsurface, storing dataassociated with the sensed physical parameters, and mapping theutilities within the subsurface as a function of subsurface depth usingthe stored data. The utilities are typically mapped within thesubsurface as a function of position and subsurface depth.

[0019] Mapping the utilities typically involves computing depth of theutilities as a function of position. Mapping the utilities may furtherinvolve computing a depth tolerance factor associated with at least someof the sensed physical parameters. The depth tolerance factors aretypically computed as a function of position. Tolerance factor data maybe computed for each data point of the stored data. Tolerance factordata may also be computed for each of the utilities in toto. Groundtruth data may be used to enhance the accuracy of utility mapping.

[0020] A 2-D map or a 3-D map of the utilities may be generated. Mappingdata may be incorporated within a Geographic Information System or otherpositional reference system. The Geographic Information System, forexample, preferably defines subsurface mapping data in three dimensionsusing subsurface depth data. Data associated with one or more of thesensed physical parameters, one or more of the detected utilities, or amap of the detected utilities may be displayed.

[0021] In accordance with yet another embodiment of the presentinvention, an apparatus for detecting underground utilities includes asensor system comprising a number of sensors. Each of the sensors sensesa physical parameter of the subsurface differing from that sensed byother sensors of the sensor system, it being understood that redundantsensors sensing the same physical parameter or parameters may beemployed.

[0022] A memory stores sensor data acquired by the sensors. A processoris coupled to the sensor unit and memory. The processor controlscontemporaneous acquisition of the sensor data from the sensors anddetects underground utilities within the subsurface using the sensordata. The apparatus may further include a positional reference system.The positional reference system produces position data associated with aposition of each of the sensors.

[0023] In one system deployment, the system includes a radar unit thatgenerates radar waves and a seismic unit that generates seismic waves.Preferably, the radar and seismic waves have about the same wavelength,as discussed above. The seismic unit preferably generates seismic shearwaves.

[0024] The sensor system may include two or more of a ground penetratingradar (GPR) sensor, a seismic sensor, a nuclear magnetic resonance (NMR)sensor, an electromagnetic (EM) sensor, a time-domain electromagnetic(TDEM) sensor, and cone penetrometer instrument. The sensor system mayalso include one or more of a resistivity sensor, a permittivity sensor,a conductivity sensor, and a magnetometer. One or both of an infraredsensor and a video device may further be included.

[0025] The processor, in one embodiment, is coupled to a data fusionengine for processing the contemporaneously acquired sensor data. Theprocessor performs joint inversion of the sensor data to determine adepth and a location of the detected utilities. The processor computestolerance factor data associated with sensor data stored in memory. Theprocessor weights the stored data using the tolerance factor data.Tolerance factor data may be computed for each of the detectedutilities. The memory may store ground truth data and the processor mayprocess the ground truth data to enhance accuracy of utility detection.

[0026] A processor, which may be a processor different from that coupledto the sensor unit, generates a map of the detected utilities using thesensor data. Data associated with the map may be incorporated within aGeographic Information System or other geographic reference model. Theprocessor may generate a 2-D map or a 3-D map of the detected utilities.A display is coupled to the processor. The processor causes the displayto display data associated with one or more of the sensed physicalparameters or one or more of the detected utilities.

[0027] According to another embodiment, a utility mapping databasesystem stores, manages, and disseminates utility detection and mappingdata. Detector data acquired and processed during a mapping operation ispreferably stored in a utility location database. It is understood thatdata stored and processed within the utility mapping database accordingto this embodiment may be developed by multiple utility detectors, asdiscussed above, or a single utility detector, such as a GPR or seismicsensor. As such, the features and advantages realized by implementationand use of a utility mapping database system according to thisembodiment of the present invention do not require that the utility databe obtained using a multiplicity of utility detectors.

[0028] The utility location database may be a single or distributeddatabase. The utility location database preferably stores mapping datafor numerous areas or regions within cities, countries, and continents.The mapping data for given locations may vary in terms of confidencelevel (e.g., accuracy or reliability), with lower confidence levelmapping data being replaced with higher confidence level mapping dataover time.

[0029] A mapping data distribution system provides user access tomapping data and ancillary resources which may be accessed via publicand private interfaces. In one embodiment, internet/web access to themapping data distribution system provides for world-wide access to thesystem's mapping data and resources. Accounting and billing mechanismsprovide a means for charging users for accessing and utilizing data andresources of the mapping data distribution system.

[0030] The above summary of the present invention is not intended todescribe each embodiment or every implementation of the presentinvention. Advantages and attainments, together with a more completeunderstanding of the invention, will become apparent and appreciated byreferring to the following detailed description and claims taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0031]FIG. 1 is a cross-sectional view of a geographic area representingan urban subsurface within which various utilities are installed, theutilities being detected and mapped in accordance with the principles ofthe present invention;

[0032]FIG. 2 is a block diagram generally illustrating an aspect of theinvention whereby subsurface structures, such as utilities, are mappedand stored in accordance with an embodiment of the present invention;

[0033]FIG. 3 is a block diagram generally illustrating an aspect of theinvention whereby subsurface structures, such as utilities, are mappedand stored in accordance with another embodiment of the presentinvention;

[0034]FIG. 4 is a block diagram generally illustrating an aspect of theinvention whereby subsurface structures, such as utilities, are mappedand stored in accordance with a further embodiment of the presentinvention;

[0035]FIG. 5 is a block diagram illustrating another embodiment of amapping system, including data processing and storing elements, inaccordance with the principles of the present invention;

[0036]FIG. 6 is a more particular embodiment of a mapping system inaccordance with another embodiment of the present invention;

[0037]FIG. 7 is a block diagram illustrating various manners in whichthe detection of subsurface structures can be accomplished according tothe principles of the present invention;

[0038]FIG. 8 illustrates various exemplary probe signal and/or detectiontechnologies that may be used in connection with the embodiments of thepresent invention;

[0039]FIG. 9 illustrates an embodiment of a subsurface detectionmethodology that provides for detection of one or more subsurfaceutility structures equipped with embedded utility Ids;

[0040]FIG. 10 illustrates an “early warning” or “critical pathwayguidance” system according to an embodiment of the present invention;

[0041]FIG. 11 is a block diagram generally illustrating various mannersin which mapped utility location data may be stored and maintained;

[0042]FIG. 12 illustrates a further embodiment of the present inventionin which multiple public and/or private access paths are provided to andfrom a utility location database;

[0043]FIG. 13 illustrates various business related processing resourcesand interfaces that may enhance the ability to account and bill usersfor accessing and using a utility location database and ancillaryresources according to an embodiment of the present invention;

[0044]FIG. 14 illustrates an embodiment of a data fusion engine thatprocesses a multiplicity of detector output signals to provide a utilitylocation result for one or more utilities or structures passing throughor contained within a volume of earth subject to a utility mappingoperation;

[0045]FIG. 15 provides an illustration showing how a particular utilitydetector may be tuned or calibrated using soil sensor data in accordancewith an embodiment of the present invention;

[0046]FIG. 16 shows a section of a city or other area through which oneor more utilities pass, the city section including regions in which thelevel of confidence in utility mapping data varies; and

[0047]FIG. 17 is a depiction of a user interface display in which aregion of interest is presented and a snapshot view of a selected regionindicates the existence of mapping data for the region having mixedconfidence levels according to an embodiment of the present invention.

[0048] While the invention is amenable to various modifications andalternative forms, specifics thereof have been shown by way of examplein the drawings and will be described in detail hereinbelow. It is to beunderstood, however, that the intention is not to limit the invention tothe particular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

[0049] In the following description of the illustrated embodiments,references are made to the accompanying drawings which form a parthereof, and in which is shown by way of illustration, variousembodiments in which the invention may be practiced. It is to beunderstood that other embodiments may be utilized, and structural andfunctional changes may be made without departing from the scope of thepresent invention.

[0050] According to an embodiment of the present invention, locationdata for an existing or new installation site is acquired using at leastone, and generally several, utility detectors. One or more of theutility detectors may be of type that generates a probe signal,transmits the probe signal into the subsurface of interest, and detectsa response signal from the subsurface. The response signal may be anaturally occurring reflection signal or a signal produced by a devicesituated within the subsurface, such as by a device mounted to anexisting or newly installed utility. One or more of the utilitydetectors may be of type that only receives signal information or otherdata from an external source, such as from a source on or in proximitywith a buried utility.

[0051] For example, an above-ground or downhole GPR or seismic/acousticutility detectors may be used to perform subsurface imaging for purposesof detecting buried utilities and obstacles. Various techniques fordetecting subsurface structures and objects and for characterizingsubsurface geology are disclosed in commonly assigned U.S. Pat. Nos.5,720,354, 5,904,210, 5,819,859, 5,553,407, 5,704,142, and 5,659,985,all of which are hereby incorporated herein by reference in theirrespective entireties. An exemplary approach for detecting anunderground object and determining the range of the underground objectusing radar signals is described in U.S. Pat. Nos. 5,867,117 and6,225,941, which are hereby incorporated herein by reference in theirrespective entireties.

[0052] Utility detectors of differing or similar technologies andconfigurations may be situated above ground, at ground level, within thesubsurface, on or within a buried utility, or within or on anunderground boring or reaming apparatus. Utility detectors of differentor common types may be situated on separate movable platforms or on acommon movable platform.

[0053] In a typical system deployment, a number of different utilitydetectors are used to scan a given volume of earth that contains one ormore utilities. The data acquired by the multiplicity of utilitydetectors is associated with position reference data as the detectorsare displaced during the scanning operation. The signals acquired fromthe multiplicity of utility detectors are preferably, but notnecessarily, processed by a data fusion engine to produce utilitylocation data. The data fusion engine may also produce quality datawhich indicates the relative quality or reliability of the utilitylocation data (e.g., tolerance data). The quality data typically variesas a function of 3-D location of the utility within the volume of earthsubject to the mapping/scanning operation.

[0054] The detector data acquired and processed during the mappingoperation is preferably stored in a utility location database. Theutility location database may be a single or distributed database. Theutility location database preferably stores mapping data for numerousareas or regions within cities, countries, and continents (e.g., globalmapping database system). The mapping data for given locations may varyin terms of confidence level (e.g., accuracy or reliability), with lowerconfidence level mapping data being replaced with higher confidencelevel mapping data over time.

[0055] A mapping data distribution system provides user access tomapping data and ancillary resources which may be accessed via publicand private interfaces. In one embodiment, internet/web access to themapping data distribution system provides for world-wide access to thesystem's mapping data and resources. Accounting and billing mechanismsprovide a means for charging users for accessing and utilizing data andresources of the mapping data distribution system.

[0056] According to one embodiment, a utility detection system of thepresent invention is provided on a portable platform(s) and towed by asmall vehicle, such as an all terrain vehicle (ATV). In this systemdeployment, utility detection data is preferably acquired at collectionspeeds between about 2 and 5 mph for depths of at least 15 feet or more.

[0057] The accuracy of individual utility detectors varies as a functiondetector technology, speed of scanning along scan path, depth, and soilconditions, among other factors. It is preferred that the detection databe accurate to no less than 6 inches vertical when monitoring utilities8 feet or less below the surface being traveled. The mobile utilitydetection system operates over flat and sloped terrain, and operatesnominally at any angle up to at least 15 degrees from horizontal in bothfore-aft and side-to-side positions.

[0058]FIG. 1 is a cross-sectional view of a geographic area representingthe subsurface 20 of a section of the earth. In this particular example,the illustrated geographic area includes urban and residentialdevelopments at the surface 22. Utilities and services 24 (generallyreferred to herein as “utilities”) are often provided to thesedevelopments by way of buried conduits, cables, etc. These utilities 24include products and services such as gas, water, sewer, electricallines, telephone wires, cable, fiber optic cable, data lines, and otherutilities/services. The buried utilities 24 generally illustrated inFIG. 1 may be provided via utility conduits (e.g., sewer or waterconduits, electrical conduits, etc.), or may be directly installed inthe ground (e.g., cables or other utilities laid without conduits).

[0059] There are several manners in which such utilities 24 areinstalled below the earth's surface, including digging trenches withtrenching machines or backhoes, and drilling subsurface bores(trenchless drilling) using a boring machine. When installing newutilities and services 24, it is problematic to encounter existingutilities 24 or other obstructions that lie in the path where theutility is to be installed. Obstructions 26, such as rock or othermaterial that is difficult to penetrate, can cause great difficulty whendigging, trenching or boring. Notwithstanding the potential damage toexisting subsurface utilities 24, such an encounter may pose substantialsafety concerns when a trenching or boring apparatus encounters anexisting utility, such as a gas line.

[0060] Before trenching, boring, or engaging in other invasivesubsurface activity, it is thus imperative to know the location of theexisting utilities 24 and/or obstructions 26, in order to assist intrenching or boring operations and minimize safety risks. Currently,utilities 24 that are installed or otherwise discovered duringinstallation may have their corresponding physical locations manuallyrecorded in order to facilitate future installations. One such system,as was discussed previously, is referred to as the One-Call system,where an inquiry call can be made to obtain utility location informationfrom an organization that manually records utility location information,when and if it is provided. However, the One-Call system is notparticularly reliable, as only a certain percentage of the utilities 24are recorded, and those that are recorded may have suspect or impreciselocation data. Therefore, currently-existing location data for buriedutilities 24 is incomplete and often questionable in terms ofreliability.

[0061] New underground utilities 24 are being installed every day. Ascities expand or undergo reconstruction, additional water, sewer, gas,electric, cable television, telephone, fiber optic, and otherunderground utilities 24 are buried, causing and ever-increasingchallenge to new utility installations. An embodiment of the presentinvention provides a manner of accurately mapping existing and newutilities 24, obstructions 26, soil characteristics, and otherinformation pertaining to the subsurface in which digging, trenchingand/or boring may occur.

[0062] In accordance with an embodiment of the present invention,multiple detection mechanisms are utilized in concert to provideaccurate placement information pertaining to underground utilities 24and associated ground attributes. For example, multiple detectors 32,such as detector module 32 a, detector module 32 b, through detectormodule 32 n in FIG. 1, can each perform detection functions in order tolocate the underground utilities 24 or other objects of interest. Thesefunctions may be performed sequentially, concurrently, or in somecombination thereof, such that the desired one or more detectors 32identify the physical location of these underground structures in thebest possible manner using the corresponding detection technologies.

[0063] As will be described in further detail below, probe signals maybe transmitted into the ground, generating return signals that can bedetected by the detector modules 32 in response to reflection orotherwise responsive signals from the buried utilities 24 or otherstructures. In alternative embodiments, signals originating undergroundmay be detected by the detector modules 32. For example, signalsassociated with the placement of particular utilities 24 may begenerated for detection by the detector modules 32, or sensors may bepermanently located under the ground at strategic locations from whichprobe signals and corresponding detection occurs. Some detectionmechanisms detect characteristics of the soil and/or utilities 24without the need for an explicitly generated signal, such as thedetection of magnetic fields, heat, etc. Further, signals generatedwithin or received by the borehead in a trenchless drilling system maybe used to provide location information of the borehead, and boreheadsensing technology may be utilized where sensors in the borehead provideinformation as to the location of existing underground utilities 24 andother objects.

[0064] In accordance with another embodiment of the present invention,buried structure location information is collected as illustrated by thedata collection module 30 shown in FIG. 1. Location data pertaining toexisting or “as-built” utilities 24 ascertained by any utility locationdevice, or by manual measurements, are collected in the data collectionmodule 30 to create a database of the subsurface structures. The datastored in the utility location database 38 essentially provides a map ofnew and preexisting underground structures of interest. Such a databasecan be continuously updated so that it contains the most recent map ofthe subsurface structures. When further invasive subsurface activityoccurs, the database can be called upon to provide subsurface structureinformation to assist in the invasive subsurface activity with greatlydiminished concerns that existing subsurface structures will beinadvertently encountered as a result of the invasive activity. As willbe described in greater detail below, such a database can be commonlycollected in a single database via various transmission means, oralternatively, may comprise a distributed database of a plurality ofdiscrete or regional databases.

[0065]FIG. 2 is a block diagram generally illustrating an aspect of theinvention whereby subsurface structures, such as utilities 24, aremapped and stored. Subsurface mapping occurs by detecting, using any ofa variety of known or future subsurface structure detection mechanisms,each of the utilities 24 or other obstructions of interest. In theembodiment of FIG. 2, the detection of the underground utilities 24 isaccomplished through the use of a plurality of detector mechanisms, suchas detector 32 a, detector 32 b, through any desired number of detectorsrepresented by detector 32 n. In one embodiment, each of the detectors32 stores retrieved information in a local detector database 34 (DDB),which may in turn be collectively stored in a local database 36. Thecontents of the local database 36 may further be stored in a centralutility location database 38. Other local databases 36 associated withother geographic areas may also supply data to this central utilitylocation database 38.

[0066] Various images and data associated with detected utilities 24 atthe present site or other sites may be developed using one or more ofthe local detector database 34, local database 36, utility locationdatabase 38, a single detector 32 or multiple detectors 32 and presentedon display 43. Raw sensor data, partially processed sensor data, orfully processed sensor data (e.g., fused sensor data) may be presentedon display 43. Data may be presented in 2-D or 3-D on display 43 inreal-time or quasi-real-time (e.g., delay of a few minutes for certaindata). Display 43 may be mounted to the utility mapping system, a remoteunit separate from, but in communication with, the utility mappingsystem, or a subsurface penetrating machine, such as a horizontaldirectional drilling machine for example.

[0067] The central database may also receive “as-built” or other knownutility data 40. For example, utility location data may currently existfor certain utilities 24, as the location data may have been manuallyentered into a database as the utilities 24 were installed. This isgenerally referred to herein as “as-built” data 40. Further, utilitylocation information may be manually established, from processes such as“pot-holing” where excavation is performed in order to locate existingutilities 24 and record the corresponding location data (one form of“ground truth” data).

[0068] It should be recognized that the hierarchy of databases may beconfigured however desired in accordance with this embodiment of thepresent invention. In any event, the database containing the locationdata of the subsurface structures may in turn be accessed in order toassist in further digging, trenching, boring, or other subsurfaceactivity, as illustrated by the retrieval of data in connection withsubsurface evaluations, subsurface excavation activities, and othersubsurface invasive activities. By having this knowledge at hand, thoseengaged in such invasive subsurface activities can avoid encounteringand damaging existing utilities 24, and greatly mitigate safety concernsthat are inherent to such activity.

[0069]FIG. 3 is a block diagram generally illustrating another aspect ofthe invention, further incorporating data fusion principles. Asdescribed in connection with FIG. 2, subsurface mapping takes placeusing any of a variety of known or future subsurface structure detectionmethodologies, such as via one or more of detector 32 a-32 n. Eachdetector 32 provides an indication of the location of the buriedutilities 24 or subsurface obstructions. The detectors 32 mayincorporate common detection technologies, or may each incorporatedifferent detection technologies to provide a variety of technicaljudgments on where the utility 24 is located.

[0070] In the illustrated embodiment, the data is collected from each ofthe detectors 32, and provided to a data fusion module 42 that processesthe raw data detected by a plurality of the detectors 32. The datafusion module 42 processes data from multiple sensors/detectors 32 bymathematically relating the data to produce a fused identification ofthe actual location of the buried structures. The location data from thedata fusion module 42 generally provides utility location informationwith a higher degree of accuracy. For example, the data fusion module 42may implement algorithms that provide a greater weight to informationgathered by a certain detector in certain soil conditions, or toinformation gathered by a particular detector when the undergroundutility 24 is a particular size or having a particular composition orproperty.

[0071] Alternatively, the location information from a plurality of thedetectors 32 may be collectively considered to provide the best estimateof the location of utility 24 using standard averaging or weightedaveraging techniques. For example, where multiple detectors 32 providemapping information that would place a particular utility 24 at acertain location, and one of the detectors 32 provides mappinginformation that is significantly different from the remaining detectors32 information, the disparate mapping data may be considered abhorrentinformation and may thus be discarded from the analysis. As can beappreciated by those skilled in the art, a multitude of data fusionalgorithms can be used in connection with the data fusion module 42.Data fusion may be determined in a manner described herein, and in U.S.Pat. No. 5,321,613 entitled “Data Fusion Workstation,” issued Jun. 14,1994 to Porter et al., the contents of which are incorporated herein byreference.

[0072] The location data provided by the data fusion module 42 may bestored in the database. Further, existing information in the databaserelating to the particular utility or utilities 24 of interest may beprovided to the data fusion module 42 to assist in the analysis.As-built or otherwise known information 40 can also be provided to thedata fusion module 42 to assist in the analysis. As previouslydescribed, the as-built or known information 40 may includemanually-generated location records from pot-holing or manualmeasurements as utilities 24 are installed (e.g., ground truth data).

[0073] Subsequent underground activities, such as the illustratedsubsurface invasive activities, subsurface evaluations, and subsurfaceexcavation activities, can make use of the information stored in thedatabase 38. This allows for more accurate, safe, and efficient utilityinstallations. As these new utility installations take place, theplacement and/or location information pertaining to these newinstallations can be stored in the database as new “as-built” data 41.

[0074] This as-built information can be acquired by manual measurements,or preferably by automatic location information resulting fromtechnologies such as those described in U.S. Pat. No. 5,553,407 entitled“Excavator Data Acquisition and Control System and Method of Use”,issued Sep. 10, 1996 to Stump; U.S. Pat. No. 5,720,354 entitled“Trenchless Underground Boring System with Boring Tool Location”, issuedFeb. 24, 1998 to Stump et al.; U.S. Pat. No. 5,904,210 entitled“Apparatus and Method for Detecting a Location and an Orientation of anUnderground Boring Tool”, issued May 18, 1999 to Stump et al.; and U.S.Pat. No. 5,819,859 entitled “Apparatus and Method For Detecting anUnderground Structure”, issued Oct. 13, 1998 to Stump et al., thecontents of each being incorporated herein by reference, and whichgenerally describe various underground utility and subsurface geologicevaluation and mapping techniques. In this manner, the database can beupdated contemporaneously as new utility installations take place.

[0075]FIG. 4 is a block diagram generally illustrating anotherembodiment of a mapping system in accordance with an embodiment of thepresent invention. Subsurface mapping occurs using any of a variety ofsubsurface structure detection systems. In this embodiment, subsurfacemapping may result from one or more detection techniques, some of whichmay operate in connection with subsurface probe signals. For example, anumber of mapping methodologies may include a probe signal generator 33a, 33 b to transmit a location probe signal into the subsurface. Acorresponding detection module 35 a, 35 b receives the reflected orotherwise responsive signal(s). The responsive signal is indicative ofthe location of the underground utility 24 or other structure.Alternatively, one or more detection modules 32 c, 32 n may beconfigured to receive signals generated below ground, such as via adrill head signal, a signal generated by a signal generator positionedon a utility itself, energy naturally emanating from subsurfacestructures, or other subsurface-initiated signals. The detected signalsare collected in a data collection module 36, where data fusionoperations may optionally be applied by data collection module 36. Aspreviously described, “as-built” and other known utility location data40 may be provided to the data fusion module 42 as a parameter to theassociated data fusion functions, and/or may be provided directly to thedatabase 38.

[0076] A historical database 44 may also be used in connection with thedata fusion module 42. The historical database 44 may contain anydesired historical data, such as known soil characteristics proximatethe target location, known GPR profiles that are associated with knownsoil or utility types, excavator difficulty data, or excavator hardwareand software configurations (e.g., particular machine type, cutting bitor jet, cutting action, digger chain bits, mud system components and mudadditives, etc.) known to be particularly useful for particular soil orjob conditions, for example. The historical database 44 may further oralternatively contain preliminary utility location data that may beuploaded to the central database 38 or used in connection with datafusion algorithms.

[0077] Where the historical database 44 includes soil or othersubsurface characteristics data, the data fusion module 42 may utilizethis data in arriving at a resulting utility location. Such historicaldata may be useful in improving the accuracy of the utility/objectlocation determination and/or the quality or tolerance factor associatedwith the computed location. Particular soil conditions at a targetlocation may alter or shift a weighted data fusion algorithm to arriveat the most accurate utility location. The data fusion engine mayfurther interact with the historical database 44 which may storeearlier-acquired data of varying types which may be useful in theprocessing the detector data.

[0078]FIG. 5 is a block diagram illustrating another embodiment of amapping system in accordance with the present invention. In thisexample, utility conduits 24A, 24B, and 24 n are illustrated. Utilityconduit 24n represents the n-th utility in an unspecified number ofutilities at the subsurface of a particular geographic area. Asutilities are detected as described above, the corresponding locationdata from each enabled detector is processed to determine its actuallocation. For example, all enabled detection devices (whether sensing asignal responsive to an above-ground probe signal, or sensing a signalgenerated or emanating below ground) that provide location informationfor utility conduit 24A are processed via an object A processing module52.

[0079] In a more particular example, a ground penetrating radar (GPR)signal may be generated above ground, and a responsive signal indicativeof utility conduit 24A is sensed by a GPR detection module. A secondprobe signal, such as a seismic or acoustic signal, may be generated anddirected towards the subsurface to produce a second responsive signalindicative of the location of utility conduit 24A. Because multipledetectors 32 are implemented in such an embodiment, the multipleresulting location data must be resolved, via object A processing module52, to determine the most probable and accurate location of utilityconduit 24A. By utilizing multiple detection methodologies and applyingdata fusion principles on the resulting data, more accurate locationinformation can be obtained. Analogous operations are conducted forutility conduit 24B, and all subsurface structures of interest throughutility conduit 24 n.

[0080] The location results for each of the underground utilities 24 arestored in the database 60 at a first time, e.g. t=1. This first timegenerally reflects the occurrence of the detection and storingoperations. At a later time, illustrated at time t=2, subsequentsubsurface activity (e.g., trenching, boring, or other subsurfaceinvasive activity) can be guided by the location data stored in thedatabase 60. For example, ground penetration equipment such astrenchless boring equipment can download the utility locationinformation to a bore plan model in order to allow the groundpenetration activity to occur without colliding with existing buriedutilities 24. Where utilities 24 are installed in connection with theground penetration activity, the location data can be returned to thedatabase 60 as “as-built” location data. Thus, the database 60 can beupdated and/or verified by information ascertained by the groundpenetration equipment at a later time (e.g., t=2).

[0081]FIG. 6 is a more particular embodiment of a mapping system inaccordance with an embodiment of the present invention. As was describedin connection with FIG. 5, a plurality of detection units 32 areprovided to receive raw data pertaining to the location of a pluralityof buried utilities 24, such as utility conduits 24A, 24B through 24 n.In some cases, the detection modules 32 n may detect signals generatedor emanating from below ground. In other cases, the detection modules 32a, 32 b may be associated with corresponding probe signals PS1, PS2associated with various ground penetrating technologies.

[0082] A geographic location module 39 provides a geographic referencefor the detected utility locations via positional reference units 37.For example, the geographic location module 39 may include a geographicinformation system (GIS) or geographic reference systems (GRS), whichare known systems for characterizing the three-dimensional location ofobjects within a given volume of earth.

[0083] Geographic information systems, for example, allow for storage,display, and manipulation of three-dimensional data. GIS systems providefor the integration of sensor data with other kinds of map data, such aspre-existing utility maps, building and street maps, and pot-holeinformation (e.g., ground truth data), for example. Since GIS systemscan store data in three dimensions, the depths and verticalrelationships of the various infrastructure features and sensor data canbe accurately maintained. A preferred GIS system integrates GPR, EM(electromagnetic) and seismic sensor data, for example, with existinginfrastructure maps. Infrastructure maps can be developed during systemtesting and mapping.

[0084] The geographic location module 39 may also include a globalpositioning system (GPS) to provide position data for determining therelative geographic position of the buried structures. The positionalreference data developed by positional reference units 37 are used inconnection with the detected, relative location signals to provide anabsolute location indication for the buried utilities 24.

[0085] Other useful positioning systems include Differential GlobalPositioning System (DGPS), laser positioning (LPS) and a survey wheel. Asuitable DGPS can simultaneously track 12 GPS satellites and 12 GLONASS(Russian) satellites, and has an accuracy of 1-2 cm in differentialmode. DGPS is convenient to use when there is a sufficiently clear spaceoverhead to view a sufficient number of satellites. All communication tothe base station is via radio, and as such, no wires are required. AnLPS is preferably used when the DGPS does not operate successfully, suchas when in a tunnel, near tall buildings, or possibly under heavytree-cover.

[0086] Accurate position sensing is important. When a given utilitysensor is used to survey a series of parallel lines, for example, theposition at each data point must be well known in order for processingsoftware to combine the data points into accurate 3-D pictures. Evenmore important is the deleterious effect that erroneous position datamay have on automatic target recognition software results, for example.Similarly, each of the suites of utility sensors may be used separatelyin surveys, if needed or desired. In order for the sensor data fusion tooperate properly, the position of each sensor must be known withsufficient accuracy so that the data collected may be properly overlaid.

[0087] As seen in FIG. 6, a first probe signal source 33 a of detectionmodule 32 a may generate a probe signal PSI that is reflected orotherwise causes a responsive signal to be returned from the subsurfaceto the detection module D1 35 a. As the probe signal PS1 is transmittedthrough the subsurface, the probe signal source 33 a can be moved alongthe ground surface to map the subsurface of the corresponding area oftravel. The returned/responsive signal detected by the detection moduleD1 35 a is thus a function of the probe signal source's position as theprobe signal source 33 a traverses the ground surface. As utilities 24and other structures of interest are identified by the detection moduleD1 35 a, the resulting raw location data may be temporarily stored, suchas in the object A, B and n map result storage locations 62 a-n, 64 a-n,66 a-n. Similar operations take place for each of the detection modules32 ba-n, such as the detection module D2 32 b associated with probesignal PS2, and the detection module(s) Dn 32 n detectingsubsurface-initiated signals. Each of the detection modules 32 a-n maydetect multiple underground utilities 24 and structures, storing theresults in a corresponding map result storage location 62 a-n, 64 a-n,66 a-n. Each detection module 32, therefore, provides raw location datacorresponding to each of the underground utilities/structures 24identified by the respective sensor technology.

[0088] The resulting data for each location is then processed to arriveat a collective location result. For example, the object A processingmodule 52 receives the raw location data for a first object, such asutility conduit 24A, from each of the detection modules 32 a-n. In oneembodiment, the location data is first stored in corresponding temporarystorage locations, and the information is then passed to the object Aprocessing module 52 where it is processed to more accurately identifythe actual location of the utility conduit 24A. The object A processingmodule 52 processes the location results for utility conduit 24A fromeach of the utility sensing devices 32, and outputs a single locationfor utility conduit 24A based on all of the location data provided bythe multiple detectors 32 for utility conduit 24A. Such processingoccurs for each subsurface structure of interest, via individualprocessing modules, an aggregate processing module, distributedprocessing, or other processing arrangement. The resolved locations foreach of the subsurface structures, e.g., utility conduits 24A, 24Bthrough 24 n in the example of FIG. 6, are stored in a utility database60 to maintain the data.

[0089]FIG. 7 is a block diagram illustrating various manners in whichthe detection of subsurface structures can be accomplished. Thesesubsurface structures of interest may include utility conduits, buildingfoundations, rocks and other substantially impervious objects, and thelike. Generally, any underground object complicating subsequenttrenching, boring or other invasive subsurface activity, and/or causingsafety concerns, may constitute a subsurface structure of interest inwhich detection is desired. For instance, in the example of FIG. 7,utility conduits 24A, 24B, 24n are of interest as subsequent invasivesubsurface activity could cause damage or present safety concerns ifstruck. It may also be desirable to detect and record the location ofimpervious object 26X, as it may present difficulties in trenching orboring activities.

[0090] In accordance with the present invention, these subsurfacestructures are detected using one or more different detectiontechnologies. Because of varying ground characteristics, varying utilityand conduit types, soil composition, moisture, structure depth,structure composition, structure contents, and the like, the use ofmultiple detection technologies provides a greater assurance of actualstructure location. This is particularly true where data fusionprinciples are applied, where one or more of the plurality of detectiontechnologies may present more accurate readings, and thus be accordedgreater weight, depending on parameters such as the groundcharacteristics, utility/conduit types, soil composition, etc. In someinstances, the data fusion methodologies applied may simply disregarddetection technologies known to be relatively unreliable in theparticular environment in which detection is sought.

[0091]FIG. 7 illustrates that each of the detection technologies isassociated with a positional reference. As earlier described, ageographic location module 39 provides a geographic reference for thedetected subsurface structure locations. For example, the geographiclocation module 39 may include GIS, GRS, GPS, LPS, or otherposition-identifying technologies, resulting in positional referencesthat are used in connection with the detected, relative location signalsto provide an absolute location indication for the undergroundstructures.

[0092] In the particular embodiment of FIG. 7, multiple detectiontechnologies are illustrated. A first detector D1 35 a is used inconnection with a probe signal PS1 that presents one of a variety ofdifferent available probe signal technologies. For example, the probesignal PS1 may be a ground penetrating radar (GPR) signal that istransmitted into the ground, resulting in reflected signals from utilityconduits 24A, 24B and from object 26X. In one embodiment, the probesignal/detection module 32 a travels along the ground surface, such thatthe associated positional reference changes with positional referenceunit travel, and provides a map of the subsurface in response thereto.Other probe signal/detection modules 32 b-n may also be used. Forexample, the detector D2 35 b may be used to detect reflected orotherwise responsive signals from one or more probe signals PS2 providedby probe signal source 33 b. The particular probe signal technology thatis employed governs the type of signal actually transmitted into theearth.

[0093] In other embodiments, no probe signal is transmitted from aboveground, such as depicted by detectors D3 35 c and Dn 35 n. In theseembodiments, signals originating or otherwise emanating/radiating fromthe subsurface objects themselves are detected. For example, utilityconduits 24 may be equipped to generate signals that can be detected bythe detectors D3 35 c and Dn 35 n, or the underground object may exhibitcertain distinguishable characteristics that can be detected (e.g.,heat, magnetic field, etc.). In each of these instances, a particulardetection technology may be better suited to detect a particular type orgroup of underground structures. The use of multiple detectionmechanisms therefore provides location data in a variety of geographicareas with a greater degree of certainty than the use of a singletechnology.

[0094]FIG. 8 illustrates various example probe signal and/or detectiontechnologies that may be used in connection with the present invention.Ground penetrating radar (GPR) 70 may be used to obtain geologic andsubsurface structure imaging data developed from electromagnetic returnsignal information resulting from a probe signal transmitted into theearth. Seismic (e.g., shear wave seismic) or acoustic probe signals 72may be used to detect buried structures of sufficient acoustic contrastrelative to the frequency of the acoustic probe signals.

[0095] The complementary use of GPR 70 and a seismic detection system 72provides the ability to detect and map utilities in a wide range of soiltypes. For example, a subsurface that contains a predominate amount ofclay decreases the GPR system's ability to reliably detect an object(particularly object depth) within such a subsurface, but has noappreciable affect on the seismic system's detection capability. By wayof further example, a subsurface that contains a predominate amount ofsand decreases the seismic system's ability to reliably detect an objectwithin such a subsurface, but has no appreciable affect on the GPRsystem's detection capability.

[0096] Two major factors determine the propagation of electromagneticenergy, including GPR beams, below the subsurface-the dielectricconstant and the soil conductivity. The dielectric constant determinesthe speed of propagation. This information is necessary to determine theactual depth to objects, rather than only relative depth or simplynoting the presence of reflectors. The soil conductivity determines theenergy lost as the radar beam propagates through the ground, whichlargely determines the depth of penetration, and hence visibilitybeneath the surface. GPR signals experience limited penetration into theground when the electrical conductivity of the soil is too high. Soilscontaining too much clay, water or mineral constituents, for example,cause GPR signal penetration to decrease, due to the high conductivityof clay soil. Lowering the frequency of the signals used can increasethe depth of penetration, but lower frequencies have poorer resolution,thereby limiting utility size and spacing detection resolution.

[0097] The detection capability of a GPR system 70 suitable for use inthe embodiment of FIG. 8 may be improved by employment of improvedantenna designs, such as by adding multiple antennae to a single GPRsensor unit to enhance the utility of the GPR system 70. Multipleantennae allow for better detection of utilities that are not at optimumangles to the traverse of a single antenna. Also, having an independentmeans of estimating soil conductivity and dielectric constant, such asby use of and electromagnetic (EM) sensor 76, can be of much assistancein processing GPR data. Furthermore, having a measurement of theseparameters as a function of depth, rather than a single estimaterepresenting some form of average parameter, may be used to enhance theradar image. Lower frequency (relative to GPR) EM sensors 76 can be usedfor these purposes. EM sensors 76 may be used to map utilities bythemselves under favorable conditions in conductive soils.

[0098] Although the above-described design changes may improve GPRsystem detection capabilities for certain soil types, overall GPR systemperformance significantly degrades when scanning highly conductive soilenvironments, notwithstanding such design improvements. For soil typesthat are so conductive as to practicably or totally eliminate GPR 70 asa detection or mapping tool option, sensors based on other technologiesare employed that are less sensitive or insensitive to highly conductivesoil types.

[0099] One such technology that offers superior detectioncharacteristics in clay and other highly conductive soil types is ashear wave seismic technology. Since seismic waves are propagated by aphysical mechanism completely different from that of radar beams,seismic wave are not affected by soil conductivity.

[0100] The ability to detect and map utilities is also a function of theresolving power of a sensor measurement. Resolution is a function of thewavelength of the signal being measured. This relationship applies toboth electromagnetic and seismic systems. Shorter wavelengths canresolve smaller targets in the subsurface. Seismic systems havetraditionally been used to map geologic features that are at muchgreater depths than utilities, and is done with relatively lowfrequencies. Mapping very near the earth's surface, as opposed todeeper, using seismic waves is a very challenging and heretoforeunaddressed endeavor.

[0101] In addition to providing detection data in soil types that renderGPR systems 70 unreliable or unusable, a seismic system 72 of thepresent invention provides for the generation and processing ofwavelengths approaching those obtained with GPR, such as wavelengthsabove 1 kHz (e.g., in the range of about 3 kHz to 5 kHz). It isunderstood, however, that meaningful detection information may bedeveloped using a seismic system, such as a shear wave seismic system,that provides for the generation and processing of wavelengths of about1 kHz or less, and that such a seismic system may be employed within thecontext of the present invention.

[0102] A seismic signal vibrator, for example, can be used to operate inthe desired frequency range for utility detection and mapping purposes.The use of disparate detection signal types (e.g., radar signals andseismic signals) of approximately the same wavelength provides theopportunity to detect underground objects and geologic features withsimilar resolution. The disparate detection signal types ofapproximately the same wavelength can be processed in a similar manner,thereby increasing processing efficiency and decreasing processingcomplexity and cost.

[0103] For best sensitivity, the wavelength should be comparable to thediameter of the utility pipe. This constraint places limitations on themaximum depth at which the utility will remain detectable, which, in thecase of GPR 70, could be significantly less than 15 feet in more highlyconducting soils. Similar considerations apply to medium and highfrequency seismic waves, depending on soil conditions. For cases whereboth GPR 70 and seismic systems 72 have difficulties, other detectiontechniques, such as EM 76, NMR 74, and tomographic techniques, may beemployed.

[0104] In general, detection of an object of sufficient acousticcontrast is possible when the object is greater than ⅛ the wavelength ofthe dominant frequency of the propagating acoustic signal. Thewavelength-frequency relationship is as follows:

ν=fλ

[0105] where:

[0106] ν=propagation velocity

[0107] f=frequency

[0108] λ=wavelength

[0109] Using the relationship above, detecting a ⅜-inch object, forexample, requires a wavelength of about 3 inches or ¼ foot.

[0110] Shear waves, in contrast to compressional waves, are particularlywell suited for detecting objects having a size approximating that ofmost utilities of interest because shear waves travel at about ¼ to ⅛the velocity of compressional waves in unlithified soils. The slowervelocity implies shorter wavelengths for a given frequency. Creatinghigh source frequencies can be a difficult task, so utilizing shearwaves reduces design difficulties.

[0111] Velocities of shear waves suitable for utility detection are onthe order of 500-800 feet/sec (fps). This wave velocity range impliesthat suitable seismic detection transducers (e.g., vibrator and velocitytransducers, such as active or passive geophones) are sensitive tofrequencies in the 2,000-3,200 Hz range. It is noted that detection ofan object of this size with compressional waves would requirefrequencies on the order of 20 kHz. In one embodiment, a suitableseismic transducer sensitive to frequencies in the 2000-3200 Hz rangeincorporates accelerometers. The accelerometers may be active or passivein design. A shear wave seismic transducer suitable for use andadaptation in the context of the present invention is disclosed in U.S.Pat. No. 6,119,804, issued Sep. 19, 2000 to T. Owen, and entitled“Horizontally Polarized Shear-Wave Vibrator Seismic Source,” which ishereby incorporated herein by reference.

[0112] It is desirable, but not required, to provide a high frequencyvibrator of the seismic system 72 having a relatively small footprint,such as on the order of about ½ inch. A vibrator of such size increasesportability of the seismic system 72. For example, a high frequencyseismic vibrator suitable for many applications that produces a peakforce output of 25 pounds may weight about 40 pounds. A shear waveseismic sensor suitable for use in the field when detecting undergroundutilities, objects, and geologic strata preferably includes a highfrequency seismic vibrator and two spatially separated receivetransducers. A recorder and processor are preferably included as part ofthe sensor assembly.

[0113] Electromagnetic (EM) probe signals 76 of relatively low frequency(e.g., 300 Hz to 20,000 Hz) can be used to acquire subsurface data toidentify subsurface structures and soil characteristics. In oneembodiment, the EM sensor 76 may be implemented to include a singletransmitter coil and a single receive coil. Such an implementationrepresents a comparatively low cost sensor configuration of reducedcomplexity. In accordance with another embodiment, a multiple-coil,variable frequency tool is designed to detect utility pipes and cables.For example, one EM sensor configuration includes a transmitter andreceiver coil with a six-foot separation. This sensor operates fromfrequencies of 330 Hz to 20,000 Hz. This coil separation is good fordeep penetration, but may have reduced resolution for near-surfaceoperation. Another EM sensor configuration includes one receive coil andtwo or three transmit coils. One transmit coil can be co-located withthe receive coil for increased spatial resolution. One or two additionalcoils may be spaced out to provide multiple offsets that will providedepth information. The fact that each pair operates at multiplefrequencies provides additional depth information.

[0114] The EM sensor 76, according to one embodiment, has maximumsensitivity in the surface to 15 feet depth zone. As will be discussedbelow, the data from this sensor 76 can be used as part of the datafusion as both background conductivity information for the inversions,as well as information on those utilities and structures that it candetect, such as trench boundaries, bedrock, water layer and otherphysical features that have conductivity contrast with the surroundingsoil.

[0115] Nuclear magnetic resonance (NMR) 74, also referred to as magneticresonance imaging (MRI), may be adapted for near surface imaging(surface NMR or SNMR) for purposes of locating buried utilities 24 andother structures, and determining soil characteristics. NMR is amagnetic measurement that perturbs magnetic dipole moments and measuresresonance frequencies that are diagnostic of the presence of specificmaterials. NMR or MRI images are made by inducing spin in those protonswith a strong magnetic field and then measuring the signals producedwhen the spin states decay with time.

[0116] The presence, absence or variation in water content, for example,can be detected with magnetic resonance signals. Mapping vadose zonesubsurface water content, for example, may be accomplished using surfacenuclear magnetic resonance (SNMR). NMR Images can be made in thesubsurface. The transmitters and receivers of the NMR sensor 74 can beconfigured to measure important signals from the surface or withvertical probes pushed into the ground at intervals along the surveypath.

[0117] Time-domain electromagnetic (TDEM) techniques 78 arehigh-technology forms of dowsing, or groundwater exploration, used tosearch for underground bodies of water (aquifers). The technique employsa grid pattern of electric wires placed on the surface of the ground.The wires are charged with a rapidly pulsating electric current and theresultant electronic “echoes” are carefully analyzed. The data is thenused to construct a three-dimensional computer model of thewater-bearing potential of underground rock formations and sedimentlayers.

[0118] A soil conductivity, resistivity, and/or permittivity sensor 80may be used to determine the electrical properties of the soil subjectto a mapping operation. As was discussed previously, two factors thatimpact the propagation of electromagnetic energy, including GPR beams,below the subsurface are dielectric constant (permittivity) and soilconductivity. The dielectric constant determines the speed ofpropagation. Obtaining this information using a permittivity sensor 80provides for the determination of the actual depth to objects, ratherthan only relative depth or simply noting the presence of reflectors.The soil conductivity determines the energy lost as an EM signalpropagates through the ground, which largely determines the depth ofpenetration, and hence the imaging quality of the subsurface. EM signalsexperience limited penetration into the ground when the electricalconductivity of the soil is too high. One or more sensors 80 may beemployed to measure soil conductivity, resistivity, and/or permittivity.

[0119] Infrared (IR) 82 is a passive manner of detecting thermalconditions of the subsurface. Video 84 may also be used to evaluateexcavated areas and to visually monitor the operation of various mappingand excavator devices and systems. Distinguishing relative magneticfield strengths at targeted subsurface areas can be performed using amagnetometer 86, which detects magnetic fields generated by the normalmagnetic field of the earth and disturbances thereto made by ferrousobjects.

[0120] Other subsurface penetrating technologies and signal detectiontechnologies may also be used within the scope of the invention. Forexample, push technologies may be employed, where an instrumented coneis pressed into the ground to allow various measurements to be made.Cone penetrometer (CPT) technology provides for the determination of thedepth dimension in very difficult situations.

[0121] According to one aspect of the invention, a utility detectionsystem that incorporates one or more of the instruments depicted in FIG.8 may be accessed and controlled from a remote site. For example, aremotely implemented customer support service may utilize a wireless (orland line) link to access the utility detection system. Using such alink, diagnostics of the system's instruments may be performed. Each ofthe utility detection systems in the field can be accessed over theInternet, tests can be initiated, and download results may be receivedby a home office. The utility detection systems preferably includebuilt-in diagnostics to assist in production and troubleshooting.Built-in self calibration routines may also be executed for each of theinstruments provided in a particular utility detection system. Theseenhancements are designed to minimize the non-productive requirements onthe operator and to reduce downtime.

[0122]FIG. 9 illustrates an example of a subsurface detectionmethodology that may be used in connection with the present invention.In this embodiment, one or more of the subsurface utility structures areequipped with embedded utility IDs 101. These utility IDs 101 mayinclude embedded information such as utility type (e.g., water, sewer,gas, cable, fiber optic, etc.), installer identification, installationdate and other installation information, utility capacity, conduitmaterial or composition, environmental information such as soilinformation, estimated or desired depth/location information, installeddepth/location information, and the like. In this embodiment, utilityinformation may be provided as the utility is installed, i.e.,“as-built.” Probe/detector modules 32 a, 32 b may be used tosubsequently identify the location of these buried utilities 24 bytransmitting a probe signal to the utility, in which a responsive signalis returned via the utility ID 101 a with the embedded information.Alternatively, the embedded utility ID 101 b may provide an originatingsignal that can be detected by a detector 32 n above ground. In eithercase, the embedded utility IDs 101 can provide more specific informationrelating to its associated buried utility.

[0123] The embodiment of FIG. 10 illustrates an “early warning” or“critical pathway guidance” system that may be used in connection withthe present invention to provide subsurface structure location data.This particular embodiment is particularly advantageous in connectionwith a utility mapping service and/or utility location database 120maintenance service.

[0124] The “critical pathway guidance” system is a local area trackingand communication system that need not be directly attached to any oneutility 24, but includes sensing devices and a computer/database in thearea. This local database 110 stores utility location informationlocally, and may optionally be connected via phone, internet, or otherconnection 111 to a larger facility, such as the utility locationdatabase 120. The system determines the location of the utilities 24 inits working area, and can track and communicate with horizontaldirectional drilling (HDD) drill heads and reamers 116 entering andpassing within its working area. Such a system can be permanentlyinstalled in a geographic area, and the subsurface structure locationdata can be stored in the local database 110 so that subsequentsubsurface activity can draw upon, and update, the information stored inthe local database 110 when new subsurface activity occurs.

[0125] The critical pathway guidance system may also be used in theprocess of updating the utility location database 120. In one particularimplementation, the system communicates with a drill head 116 enteringthe system area of influence having a cooperative communication andtracking technology. This cooperative communication is realized bydrilling down into the ground, and installing sensing/detection devices118 underground via the drilled holes 21. These devices 118 may bephysically separate from the utilities 24 themselves, and mayincorporate various technologies such as those using high frequencyelectromagnetic (EM) signals, so that these devices 1 18 can communicatewith a drill head 116 associated with a trenchless boring system 117.The sensing/detection devices 1 18 can communicate with the drill head116 to direct the drill head 116 around obstacles or otherwise directthe drill head 116 along an appropriate path. The devices 118 may belinked via a communication link 122 to a controller 112 to appropriatelydirect the location data to the local database 110 and/or a centralutility database 120. This location data provides accurate as-builtlocation information.

[0126] Further, the underground sensors 118 can detect the presence ofthe drill head 116 (e.g., directly, or through drill head 116 signals,etc.). This information may be provided to the boring equipment 117 in afeedback configuration via the guidance system controller 112. In such asituation, the drill head 116 is detected by the underground sensors,and the drill head 116 is controlled by intelligence within the boringequipment 117 itself through feedback to the boring equipment 117. Forexample, the borehead 116 can acknowledge signals from thesensors/detectors 118, and communicate this acknowledgment to thecontroller 114 of the boring equipment 117 (e.g., via signals from theborehead 116 along the drill rods to the boring equipment 117). Inanother embodiment, the acknowledgment signals can be transmittedthrough the sensors/detectors 118 to the guidance system controller 112and/or to the equipment controller 114 to provide further control of theborehead 116. The controllers 112, 114 of the guidance system andboring/trenching equipment 117 communicate awareness and proximity dataas the borehead 116 passes through the sensitivity range of the array ofsensors/detectors 118.

[0127] When the boring is complete, the local database 110 in thecritical pathway guidance system is automatically updated with theas-built information of the new utility. The resulting data canoptionally be uploaded to a master utility location database 120 outsidethe working area of the system. This implementation provides a solutionto the problem of updating the database for new installations.

[0128]FIG. 11 is a block diagram generally illustrating various mannersin which the mapped utility location data may be maintained. A databaseis used to maintain the mapped utility location data. The database maybe comprised of a single database in which all mapping information isstored. For example, an aggregate database to collect all utilitylocation data for all mapped areas may reside on a single or distributedcomputing system, or may be comprised of a distributed database over adistributed or networked computing system. A database hierarchy may alsobe employed, such that raw location data is locally stored, thenaggregated in another database associated with a larger geographicregion, and so forth.

[0129] The illustrative database configuration of FIG. 11 depicts anembodiment wherein regional databases 200 are provided within apredetermined geographic area. For example, multiple regional databases200 may be associated with a first geographic area 202, such as theUnited States. Utility location data mapped within a first predefinedarea 202 of the U.S. may be stored in a first regional database 200 a.Utility location data mapped within a second predefined area 202 of theU.S. may be stored in a second regional database 200 a ₂. Eachpredefined subdivision of the U.S. is thus associated with a particularregional database 200. Regional databases 200 can also be implemented inother predetermined geographic areas, such as other continents,countries, etc (e.g., regions 204, 206). The result is a distributeddatabase comprising the regional databases 200 for each of thegeographic subdivisions of interest. These regional databases 200 mayoptionally be accumulated in a central database (not shown). Such acentral database may employ data coherency protocols well-known in datastorage arts to ensure that distribution of the central database's copyof a potentially shared database record is disallowed when acorresponding regional database record has been updated.

[0130] The data from regional databases 200 may also be coupled to adata manager 210 to facilitate sharing of certain information, such assoil or utility characteristics. For example, a manner of maximizingutility detection and associated data fusion principles may be found forparticular soil characteristics in the U.S. 202, such as soilcharacteristics A. This information may be stored in a regional database200 a ₁ in the U.S. 202, and subsequently downloaded to a regionaldatabase 200 n ₁ via the data manager 210 in, for example, Asia 206.This information may assist in mapping utilities in regions of Asia 206where analogous soil conditions are found.

[0131] It should be noted that various database structures may beemployed within the scope of the invention. For instance, the example ofFIG. 11 may represent multiple regional databases 200 which share littleor no information among themselves, may alternatively represent adistributed database of regional databases 200, or the data may becollected in a single database. In any event, the collective utilitylocation data is stored such that it can be used in subsequent invasivesubsurface activities.

[0132]FIG. 12 illustrates a further embodiment of the present inventionin which multiple public and/or private access paths are provided to andfrom the utility location database 300. According to this embodiment, auser may gain access to the utility location database 300 via a publicnetwork connection, such as an Internet connection 302, a web site, asatellite connection 304 or various other known communicationsmechanisms 306. Certain users, such as system administrators andtechnicians (e.g., user 1-user n in FIG. 12), may be provided withaccess rights that provide for access to the utility location database300 that effectively bypasses the public access security measures of thesystem.

[0133] A user access unit 308 receives access requests from users andprocesses such requests to determine whether to grant access rights to aprospective user. Assuming the prospective user is determined to be anauthorized user, the user access unit 308 allows the user to access theutility location database 300. If an unauthorized user is detected, theuser access unit 308 communicates a warning message to the unauthorizeduser that access to the utility location database 300 is denied orsignificantly limited.

[0134] An accounting unit 310 provides a mechanism to charge user's foraccess to and/or interaction with the utility location database 300 andany ancillary resources. A particular user may wish to interact with theutility location database 300 in different ways, each of which may havea different associated access or use cost. For example, a user may onlywish to view the availability of utility mapping data and the quality ofsuch data in a given area of a city. The user, in this case, may becharged a “view-only” access fee. Should the user later request agreater level of mapping detail for a particular street corner in thegiven area of the city, such as utility identification and sizeinformation for example, the greater quantity of detailed data may bepriced at a rate higher than that of the less detailed city area data.By way of further example, and assuming the user wishes to obtain a copyof the more detailed street corner utility mapping data, the user may becharged at a higher rate for receiving a copy of the data as compared toview-only access to the data.

[0135] The accounting unit 310 may be programmed to include or otherwiseinteract with a rate schedule that indicates the cost of various levelsof user access or resource usage with respect to various types ofmapping data and services. The accounting unit 310 monitors useractivity and accrual of charges so that users are billed appropriately.

[0136] A detector database 320 is shown coupled to the utility locationdatabase 300. A number of different detector inputs (e.g., detectors 1,2, . . . n) are shown coupled to the detector database 320. A geographiclocation database 330 provides 2-D or preferably 3-D location data whichis associated with the data acquired by the detectors 322 a-n.Alternatively, each detector 322 may provide both detector andassociated position data to the detector database 320. Associatinggeographic location information with the detector data provides for thelocating of one or more utilities within a given volume of earth.

[0137] In the embodiment illustrate in FIG. 12, the detector database320 stores raw data acquired by each of the detectors 322 a-n. A datafusion engine 325 may be coupled to the detector database 320 whichemploys data fusion algorithms to process the multiple detector datasets received from the detectors 322 a-n and stored in the detectordatabase 320. The data fusion engine 325 may use one or more knowntechniques for processing the detector data, examples of which aredisclosed in U.S. Pat. No. 5,321,613 to Porter, et al. and entitled DataFusion Workstation, which is hereby incorporated herein in its entirety.It is understood that data fusion processing may be performed uponreceiving the multiple detector output signals (e.g., in real-time), andthat the results of such data fusion processing may be stored in thedetector database 320.

[0138] The data fusion engine 325 may further interact with a historicaldatabase 326 which may store earlier-acquired data of varying typeswhich may be useful in the processing the detector data. For example,the historical data may include known GPR or other detector profileswhich are associated with known soil or utility types. Such historicaldata may be useful in improving the accuracy of the utility/objectlocation determination and/or the quality or tolerance factor associatedwith the computed location data.

[0139] The data fusion engine 325 may also interact with an as-builtdatabase 340 which contains utility mapping data derived from earliermapping operations or from manually derived mapping data acquired usingconventional approaches. For example, conventionally obtained mappingdata typically used by “one-call” services may be converted toelectronic form and stored in the as-built database 340. The data fusionengine 325 may utilize as-built data to improve the accuracy of theresultant utility location data and/or the associated quality ortolerance data.

[0140] In another embodiment, as is also shown in FIG. 12, the datafusion engine 325, historical database 326, and as-built database 340may be coupled to the utility location database 300. In this embodiment,raw or partially processed detector data is stored in the detectordatabase 320 and transmitted to the utility location database 300. Theutility location database 300, in this embodiment, may reside in amainframe computer or several high-powered computers at a commonlocation. For cost or processing efficiency reasons, it may beadvantageous to perform data fusion operations on data stored in theutility location database 300, rather than in the detector database 320.

[0141] In a further embodiment, one or more neural networks may beemployed to process various types of information acquired and/orproduced by the system depicted in FIG. 12. For example, one or moreneural networks may be employed to “learn” to process data stored in oneor more of the historical database 326, as-built database 340, andpreviously fused data with similar data attributes in particular ways toproduce various output data. Such a system is capable of improving thatquality of output data over time as the system gains experience. Forexample, using previously acquired and processed data sets for whichground truth has been verified as training sets, the neural network canbe taught to recognize similar situations in the future.

[0142] Training of the neural network(s) may be accomplished usingseveral different approaches. In general, neural network adaptationtypically takes place in accordance with a training regime in which thenetwork is subjected to particular information environments on aparticular schedule to achieve a desired end result. The neuralnetwork(s) may be embodied in hardware using known digitalimplementation techniques, such as those discussed in C. Alippi and M.Nigri, “Hardware Requirements for Digital VLSI Implementation of NeuralNetworks,” IEEE International Joint Conference on Neural Networks, vol.3, pp.1873-1878, 1991 and M. Yasunaga et al., “Design, Fabrication andEvaluation of a 5-inch Wafer Scale Neural Network LSI Composed of 576Digital Neurons,” IEEE International Joint Conference on NeuralNetworks, vol. 11, pp. 527-535, 1990.

[0143]FIG. 13 illustrates various business related processing resourcesand interfaces that may enhance the ability to account and bill usersfor accessing and using the utility location database 300 and ancillaryresources. As is also shown in FIG. 12, FIG. 13 includes a user accessunit 308 and an accounting unit 310 coupled between the utility locationdatabase 300 and an access node or interface to a public or privatecommunication line 307 (e.g., internet or web connection). The useraccess unit 308 may interact with an authorized user database 352 whichstores user information needed to distinguish between authorized anunauthorized users of the utility location database 300 resources. Theauthorized user database 352, for example, may store user names, userIDs, passwords, current address and contact information, and the likefor each user having an account that permits access to the utilitylocation database 300 resources.

[0144] A new user's access unit 350 provides for on-line registration ofa new user to the system. The new user's access unit 350 allows a newuser to establish an account which is then approved by the system and/orsystem administrator. When approved, the new user data is transmitted tothe authorized user database 352, thus allowing subsequent access to thesystem by the new user using a standard access procedure established forauthorized users.

[0145] The accounting unit 310 shown in FIG. 13 may incorporate or becoupled to a variety of accounting related data processing, storage, andinterface resources. For example, a billing unit 356 may be coupled tothe accounting unit 310 which provides a mechanism for generatingelectronic or printed billing invoices which are dispatched to users whoutilize utility location database resources. In addition, the billingunit 356 may store information concerning a user's past payment data andmay communicate a delinquency message to the user access unit 308 which,in turn, may limit or deny access to the system for a delinquent user.

[0146] A report generating facility 354 may also be coupled to theaccounting unit 310 for generating a variety of accounting, financial,resource utilization, diagnostic, and other information associated withthe operation and utilization of the utility location database 300 andancillary resources. The reporting unit 354 may, for example, include anumber of monitoring units that monitor a variety of system performanceparameters, such as number of users accessing the system, number ofbytes of data requested by users, types of data requested,unidirectional or bidirectional data transfer rates and bottlenecks indata flow, and the like.

[0147] A number of mapping service provider information resources may beaccessible to users of the utility location database system. The termmapping service provider refers to an entity/person who is hired toperform a mapping operation of a given site. A user of the system mayquery an authorized mapping service provider database 358 to determinethe identity of authorized mapping service providers or contractors thatare available to perform a mapping operation in a given locale. Pricinginformation may be accessed using a mapping service providers pricingdatabase 362. A scheduling unit 364 may be utilized by a user toschedule a particular mapping service provider to perform a desiredmapping operation. The scheduling unit 364 may, for example, utilizescheduling algorithms used in on-line reservations systems by whichreal-time availability information is provided to users for a number ofuser selectable mapping service providers.

[0148] A number of mapping data access and processing facilities may bemade available to users of the utility location database system. Amapping data availability unit 360, for example, may provide informationconcerning the present availability of mapping data for a userselectable region or location. For example, a user may wish to querywhether utility mapping data is available for a given intersection in aparticular city. Further, the user may want to know the relative qualityor reliability of the data, such as whether the mapping data wasobtained using a conventional manual approach or a high-tech approachconsistent with the principles of the present invention. Other data,such as the mapping service provider or source (e.g., municipality) thatprovided the data, the age of the data, and the equipment used to obtainthe data, may be made available to a user. The mapping data availabilityunit 360 provides users with this and other detailed informationconcerning the type of utility mapping data available for a specifiedarea or location.

[0149] A mapping data pricing unit 368 allows users to obtain pricinginformation concerning the data and data processing resources madeavailable by the system. For example, pricing information for“view-only” and downloadable data may be presented to a user. Volumediscount information may also be made available to the user, such asinformation indicating discounts based on amount of data to be accessedor purchased by a user.

[0150] A mapping data packaging/formatting unit 366 may be utilized bythe user to select a desired mode and format for receiving the purchasedutility mapping data. For example, the user may select a given fileformat or protocol that best suits the user's needs. The data may bedelivered to the purchasing user in a variety of forms, including on aCD-ROM or DVD, in a file form suitable for on-line transfer to a userdesignated destination (e.g., email address or web site) or digitalstorage media.

[0151]FIG. 14 illustrates a data fusion engine 400 with a number ofdifferent inputs and several outputs. In one embodiment, the data fusionengine 400 receives detector output signals/data from a number ofdifferent utility location detectors 402 a-n (e.g., D1, D2, . . . . Dn).As was discussed hereinabove, the data fusion engine 400 processes themultiplicity of detector output signals 402 a-n to provide a utilitylocation result 406 a for one or more utilities or structures (24A, 24B,. . . 24 n) passing through or contained within the volume of earthsubject to the utility mapping operation. A quality or tolerance factor406 b associated with the location computations is also preferably, butnot necessarily, produced as an output from the data fusion engine 400.It is noted that the quality or tolerance factor data typically variesas a function of 3-dimensional location within the scanned volume ofearth containing the one or more utilities. The data fusion engine 400may further produce a utility ID output 406 n which represents theengine's determination as to the identity of each utility subject to themapping operation. The utility ID determination may be achieved inseveral ways, such as by use of utility tags (e.g., utilityidentification cooperative targets) or by object recognition algorithmswhich operate on the raw or fused detector output data.

[0152] In a further embodiment, the data fusion engine 400 receives anoutput signal produced by one or more soil characteristic sensors 404a-n (soil sensors 1, 2, . . . n). The soil sensors 404 may provide anindication of one or more soil characteristics associated with thevolume of earth subject to the mapping operation. The soilcharacteristics data produced by a soil sensor 404 preferably varies asa function of 3-D location within the scanned volume of earth.Alternatively, the soil sensor data may represent a surface or bulkcharacteristic of the subject region of earth. The soil sensor data mayinclude resistivity, conductivity, permittivity (i.e., dielectricconstant), temperature, water saturation, soil composition, soilhardness or other soil characteristic. These data may be input to thedata fusion engine 400 which processes the data to enhance to accuracyof the resulting location, quality, and/or utility ID informationproduced at respective outputs of the data fusion engine 400.

[0153] Other data inputs to the data fusion engine 400 includesensor/detector signature data 410, historical or experience data 412,external factors information 414, and as-built data 416, for example.The sensor/detector signature data 410 may be representative or knownsensor/detector signal outputs which are associated with known soils orstructures. External factors 414 that may be useful to assess includethe type of equipment used to perform the mapping operation, the ID ofthe mapping company or technician, environmental conditions such asambient temperature, humidity, and pressure, and the like. Thehistorical data 412 and as-built data 416 may be of a type describedpreviously. In addition, the historical or experience data 412, 416 mayinclude historical survey data and models of utilities.

[0154] Data fusion can take a number of forms, depending upon the dataavailable and the intent of the user. For example, data fusion mayconsists only of co-location of the various data sets such as in ageographic information system (GIS). Data fusion preferably includes useof a GIS system as one component. Joint inversion of the sensor data maybe performed, such that measurement parameters are translated into depthand location of target utilities and other features.

[0155] A utility mapping system capable of mapping ⅜ inch diameternon-metallic pipes 15 feet below the surface may be achieved bycollecting as broad an array of different data types (e.g., seismic, EM,GPR, both time domain and frequency domain) as possible on a densespatial grid. The return signal measured by each different instrumentreflects different, but overlapping, aspects of the target utility andof the background medium in which it resides. An important aspect of thedata analysis is to use the strengths of each individual technology toimprove the resolution of the others by performing joint inversions onthe fused data sets.

[0156] Data fusion is a viable approach if done intelligently. Ingeneral, the relationship between the different return signals is highlynonlinear, with, for example, the inversion of one data type serving toyield improved estimates for model parameters that are then used asinput to the inversions of other data types (e.g., subsurfaceconductivity contrasts found from geoelectric section measurements usingTDEM methods can be used to more accurately determine boundaries ofseismic contrast, thus improving the seismic model to be inverted orvice versa). In performing these inversions, a Bayesian approach may betaken, in which the data plus any a priori probabilistic knowledge ofthe subsurface properties is used to seek optimal a postioriprobabilities for the model parameters.

[0157] EM software based on EM scattering, for example, can be appliedto the interaction between a GPR signal and the utility pipe. In thisway, the usual classical ray-tracing algorithms for mapping reflectingbodies (that have trouble, for example, distinguishing between rocks andhollow non-metallic bodies of similar size and dielectric contrast) maybe supplemented with “spectroscopic” data, i.e., resonant scatteringdata as a function of GPR frequency (obtained using a stepped-frequencyGPR system), that may serve as a more detailed fingerprint for the shapeand size of the object/utility. Long cylindrical pipes, for example,will have a highly characteristic scattering signature that may beaccurately modeled and compared to data. Similar considerations apply tomedium frequency seismic reflection data where the wavelength of theseismic wave is comparable to the pipe diameter.

[0158] Since non-metallic utilities are essentially invisible tostandard low frequency EM or TDEM probes, such measurements are used toobtain the best possible characterization of the “background” medium.Seismic and/or GPR will respond to both the background and the utilityof interest. This background may include metallic utilities and other“clutter” for which EM methods are designed to detect and map.

[0159] Inversions of the EM data are now used to obtain the bestpossible a priori parameters for input into the GPR or seismic model. Inthis way, the background may effectively be subtracted out to obtainenhanced sensitivity to the non-metallic utility of interest. It isnoted that the GPR and seismic methods have fundamental intrinsiclimitations of their own that may make the required detection difficultor impossible under certain circumstances. For example, due to signalattenuation (determined by the relation between soil conductivity andskin depth at the GPR frequency), the depth to which GPR is sensitivedecreases with decreasing wavelength. In this situation, the shear waveseismic sensor becomes particularly important, as discussed previously.

[0160] Subsurface target identification may be facilitated by use ofdata fusion. Multiple target recognition algorithms may be utilized.Target utilities may have distinct signatures under ideal soilconditions. Utility trench characteristics may have distinctcharacteristics in layered or scattering soil conditions.Three-dimensional spatial coherence may be employed to enhanceidentification of target utilities with small target signatures relativeto scattering or layering contrasts.

[0161] Ambiguity in target identification may be resolved using one ormore of specific fusion of EM and GPR, target ID, and/or operatorinterface. The fusion of EM and GPR data sets may be implemented first,followed by inclusion of soil type, shear wave seismic, NMR, tomography,and others sensor data if needed or desired. Target ID is a tool thatshould not depend on specific geophysical measurements, and implementsan extensible algorithm that incorporates multiple measurements andidentification techniques. The operator interface displays incomingdata, target ID results, DGPS or other positional reference data, allowsconfiguration of acquisition parameters, maintains site/projectinformation, captures operator comments, and other information to bedeveloped.

[0162] Fusion of EM and GPR is preferably premised on radar and EMforward modeling from a common electrical property structure. Themodeling software provides for deriving electrical property structurefrom an expected physical soil structure. Soil type, grain size,salinity, and saturation through petrophysical equations can beaccounted for. A library of target utility characteristics is preferablycompiled. Joint inversion of the EM/GPR data is performed to translatemeasurement parameters into target utility depth and location data. Theinteractions of target and soil types provides for employment of severalidentification methods to distinguish targets for display in an operatorinterface, which includes a display, such as display 43 depicted in FIG.2.

[0163] Three of such identification methods include direct detection ofan expected target in homogeneous anisotropic or layered medium, layerdisruption with trenching or pull-up, and change in scatteringcharacteristics of target or trench versus undisturbed soil. Theoperator interface preferably makes as many decisions for the operatoras possible on as many systems as possible. In one embodiment, theoperator is provided with a simple data set-up screen and real-timedisplay of the data being collected. A field screen preferably presentsas much real-time processed data as is possible for the system beingused. Raw, partially processed, and/or fused data is preferablyselectively presentable to the operator via the operator interface.

[0164] One or more databases of sensor signatures for various situationsare preferably developed and maintained. The sensor signature data ispreferably used for the data fusion processes. Data fusion processes maybe extended to provide for automatic material recognition, automaticobject size recognition, and automatic object type recognition, andfurther provide for automatically drawing cylinders representative ofdetected pipes and other utilities.

[0165]FIG. 15 provides an illustration showing how a particular detector500 may be tuned or calibrated using soil sensor data. In one approach,a detector 500 may be calibrated using an initial set of historical soilcharacteristics data 502, which may comprise sensor signature data.After initially tuning the detector 500, a soil sensor 504 may providesoil characteristics data to the detector 500 developed from the nativesoil in the locale to be subjected to mapping. The detector 500 may thenbe further tuned using this locally obtained soil characteristics data.

[0166] In addition or in the alternative, the soil sensor data may becommunicated or otherwise collected by a soil characteristics/sensorsignature database 506. This soil characteristics data by used for avariety of purposes, such as for refining a given detector/sensorsignature data set and for shared use by a user encountering similarsoil in another location (e.g., other part of the country or othercontinent). The soil sensor data may be communicated to or otherwiseaccessed by the utility location database 508.

[0167]FIG. 16 shows a section of a city or other area through which oneor more utilities 24 pass. The city section includes regions in whichthe level of confidence in the utility mapping data varies. The termconfidence level in this context refers to the level of confidence aservice company or technician would likely place on the utility mappingdata available for a particular location or area when needing to rely onthe mapping data, such as for purposes of excavating near a utility orgaining access to a buried utility. For example, the mapped regionsidentified as MAP Al and MAP A2 have associated confidence levels X1 andX2, respectively. Other mapped regions are shown to have confidencelevels X3 and X4. The confidence levels having an “X” prefix indicatethat the utility mapping data for the region was obtained using ahigh-tech mapping approach consistent with the principles of the presentinvention. The confidence levels X1, X2, X3, and X4 represent differentlevels of confidence in the high-tech mapping data resulting from anumber of factors, including type of equipment used and mapping serviceprovider hired to perform the mapping operation (e.g., authorized versusunaffiliated mapping service provider).

[0168] One particular region 600 is indicated as having a mappingconfidence level of Y. In this illustrative example, it is assumed thathigh-tech mapping of the city section shown in FIG. 16 has occurred in apatchwork manner, which is likely to be the case in many locales. Theregion 600 having a confidence level of Y is a region in which nohigh-tech mapping has been performed. Rather than have a void in themapping data between MAPs A1 and A2, it may be desirable to obtain thebest available mapping data and store this data in the utility locationdatabase. In this manner, large areas of a city or region may haveassociated utility mapping data made available to users of the utilitylocation database system, notwithstanding the disparate mapping dataconfidence levels. As high-tech mapping expands within a given areahaving mixed confidence level mapping data, the lower confidence datamay be replaced by higher confidence mapping data.

[0169]FIG. 17 is a depiction of a user interface display 700 in which aregion of interest is presented to a user. For example, the region ofinterest may be a city subsection. A snapshot view of the selectedregion indicates the existence of mapping data for the region havingmixed confidence levels. For example, the region shown in FIG. 17indicates a high confidence region 702, and moderate confidence region704, and a low confidence region 706. If, for example, a user isrequired to excavate near sensitive utilities in a low 706 or moderate704 confidence region, the user will likely need to contract to have ahigh-tech mapping operation be performed in the region, so as to replacethe mapping data of questionable confidence with high confidence data.If the user is required to excavate near the sensitive utilities in ahigh confidence region 702, the user will likely not need to have asubsequent high-tech mapping operation be performed in this region.

[0170] It will, of course, be understood that various modifications andadditions can be made to the preferred embodiments discussed hereinabovewithout departing from the scope of the present invention. Accordingly,the scope of the present invention should not be limited by theparticular embodiments described above, but should be defined only bythe claims set forth below and equivalents thereof.

What is claimed is:
 1. A method of detecting one or more underground utilities, comprising: concurrently sensing a plurality of physical parameters of a subsurface; storing data associated with the sensed physical parameters; and detecting the utilities within the subsurface using the stored data.
 2. The method of claim 1, wherein detecting the utilities further comprises associating stored data for each of the sensed physical parameters in terms of depth and position.
 3. The method of claim 1, wherein detecting the utilities further comprises: combining the stored data to produce combined data; and detecting the utilities within the subsurface using the combined data.
 4. The method of claim 1, wherein detecting the utilities further comprises: combining the stored data to produce combined data expressed in terms of subsurface depth; and detecting the utilities within the subsurface using the combined data.
 5. The method of claim 1, wherein detecting the utilities further comprises: combining the stored data to produce combined data expressed in terms of horizontal path length; and detecting the utilities within the subsurface using the combined data.
 6. The method of claim 1, wherein detecting the utilities further comprises: combining the stored data based on soil characteristics to produce combined data; and detecting the utilities within the subsurface using the combined data.
 7. The method of claim 1, further comprising determining one or more soil characteristics using one or more of the sensed physical parameters.
 8. The method of claim 1, further comprising determining one or more of soil resistivity, conductivity, permittivity, temperature, water saturation, composition, and hardness using one or more of the sensed physical parameters.
 9. The method of claim 1, wherein detecting the utilities further comprises: weighting the stored data based on signal noise associated with the sensed physical parameters; and detecting the utilities within the subsurface using the weighted stored data.
 10. The method of claim 1, wherein detecting the utilities further comprises: fusing the stored data to produce fused data; and detecting the utilities within the subsurface using the fused data.
 11. The method of claim 1, further comprising computing tolerance factor data associated with the stored data.
 12. The method of claim 11, wherein the tolerance factor data is computed dynamically.
 13. The method of claim 11, wherein the tolerance factor data is computed subsequent to storing the data.
 14. The method of claim 11, further comprising weighting the stored data using the tolerance factor data.
 15. The method of claim 1, further comprising computing tolerance factor data for each data point of the stored data.
 16. The method of claim 1, further comprising computing tolerance factor data associated with each of the detected utilities.
 17. The method of claim 1, further comprising storing ground truth data and enhancing accuracy of the utility detection using the stored ground truth data.
 18. The method of claim 1, further comprising generating a map of the detected utilities.
 19. The method of claim 18, further comprising incorporating data associated with the map within a Geographic Information System.
 20. The method of claim 1, further comprising generating a 2-D map or a 3-D map of the detected utilities.
 21. The method of claim 1, further comprising displaying data associated with one or more of the sensed physical parameters or one or more of the detected utilities.
 22. The method of claim 1, further comprising generating radar waves and seismic shear waves, the seismic shear waves having frequencies of less than about 1 kHz, wherein concurrently sensing the physical parameters further comprises concurrently sensing the physical parameters using the radar waves and seismic shear waves.
 23. The method of claim 1, further comprising generating radar waves and seismic shear waves, the seismic shear waves having frequencies of greater than about 1 kHz, wherein concurrently sensing the physical parameters further comprises concurrently sensing the physical parameters using the radar waves and seismic shear waves.
 24. A method of detecting one or more underground utilities, comprising: generating radar waves and seismic waves of about the same wavelength; concurrently sensing a plurality of physical parameters of a subsurface using the radar waves and seismic waves; storing data associated with the sensed physical parameters; and detecting the utilities within the subsurface using the stored data.
 25. The method of claim 24, further comprising determining velocities of the radar waves and seismic waves, respectively.
 26. The method of claim 24, wherein the seismic waves comprise seismic shear waves.
 27. The method of claim 24, wherein the seismic waves have frequencies of at least about 3 kHz.
 28. The method of claim 24, wherein the seismic waves have frequencies in the range of about 2,000 Hz to about 3,200 Hz.
 29. The method of claim 24, wherein the radar waves and seismic waves have wavelengths for detecting underground utilities of a predefined size.
 30. The method of claim 24, wherein the radar waves and seismic waves have wavelengths for detecting underground utilities having a dimension of at least ⅜ inch.
 31. The method of claim 24, wherein the radar waves and seismic waves have wavelengths of about 3 inches.
 32. The method of claim 24, wherein the radar waves and seismic waves have wavelengths of less than about 0.5 feet.
 33. A method of detecting one or more underground utilities, comprising: concurrently sensing a plurality of physical parameters of a subsurface; storing data associated with the sensed physical parameters; and mapping the utilities within the subsurface as a function of subsurface depth using the stored data.
 34. The method of claim 33, wherein mapping the utilities further comprises mapping the utilities within the subsurface as a function of position and subsurface depth.
 35. The method of claim 33, wherein mapping the utilities comprises computing depth of the utilities as a function of position.
 36. The method of claim 33, wherein mapping the utilities further comprises computing a depth tolerance factor associated with at least some of the sensed physical parameters.
 37. The method of claim 36, wherein the depth tolerance factors are computed as a function of position.
 38. The method of claim 33, wherein mapping the utilities further comprises computing tolerance factor data for each data point of the stored data.
 39. The method of claim 33, wherein mapping the utilities further comprises computing tolerance factor data associated with each of the utilities.
 40. The method of claim 33, further comprising storing ground truth data and enhancing accuracy of the mapped utilities using the stored ground truth data.
 41. The method of claim 33, wherein mapping the utilities further comprises generating a 2-D map or a 3-D map of the utilities.
 42. The method of claim 33, wherein mapping the utilities further comprises incorporating mapping data within a Geographic Information System.
 43. The method of claim 42, wherein the Geographic Information System defines subsurface mapping data in three dimensions using subsurface depth data.
 44. The method of claim 33, further comprising displaying data associated with one or more of the sensed physical parameters, one or more of the detected utilities, or a map of the detected utilities.
 45. The method of claim 33, further comprising generating radar waves and seismic shear waves, the seismic shear waves having frequencies of less than about 1 kHz, wherein concurrently sensing the physical parameters further comprises concurrently sensing the physical parameters using the radar waves and seismic shear waves.
 46. The method of claim 33, further comprising generating radar waves and seismic shear waves, the seismic shear waves having frequencies of greater than about 1 kHz, wherein concurrently sensing the physical parameters further comprises concurrently sensing the physical parameters using the radar waves and seismic shear waves.
 47. An apparatus for detecting underground utilities, comprising: a sensor system comprising a plurality of sensors, each of the sensors sensing a physical parameter of the subsurface differing from that sensed by other sensors of the sensor system; memory for storing sensor data acquired by the sensors; and a processor coupled to the sensor unit and memory, the processor controlling contemporaneous acquisition of the sensor data from the sensors and detecting underground utilities within the subsurface using the sensor data.
 48. The apparatus of claim 47, further comprising a positional reference system, the positional reference system producing position data associated with a position of each of the sensors.
 49. The apparatus of claim 47, wherein the sensor system comprises a radar unit that generates radar waves and a seismic unit that generates seismic waves.
 50. The apparatus of claim 49, wherein the radar and seismic waves have about the same wavelength.
 51. The apparatus of claim 49, wherein the seismic unit generates seismic shear waves.
 52. The apparatus of claim 49, wherein the seismic unit generates seismic shear waves having frequencies of at least about 3 kHz.
 53. The apparatus of claim 49, wherein the radar waves and seismic waves have wavelengths for detecting underground utilities having a dimension of at least ⅜ inch.
 54. The apparatus of claim 49, wherein the radar waves and seismic waves have wavelengths of about 3 inches.
 55. The apparatus of claim 49, wherein the seismic waves comprise seismic shear waves having frequencies of less than about 1 kHz.
 56. The apparatus of claim 49, wherein the seismic waves comprise seismic shear waves having frequencies of greater than about 1 kHz.
 57. The apparatus of claim 47, wherein the sensor system comprises two or more of a ground penetrating radar (GPR) sensor, a seismic sensor, a nuclear magnetic resonance (NMR) sensor, an electromagnetic (EM) sensor, a time-domain electromagnetic (TDEM) sensor, and cone penetrometer instrument.
 58. The apparatus of claim 47, wherein the sensor system comprises one or more of a resistivity sensor, a permittivity sensor, a conductivity sensor, and a magnetometer.
 59. The apparatus of claim 47, wherein the sensor system comprises one or both of an infrared sensor and a video device.
 60. The apparatus of claim 47, wherein the processor is coupled to a data fusion engine for processing the contemporaneously acquired sensor data.
 61. The apparatus of claim 47, wherein the processor performs joint inversion of the sensor data to determine a depth and a location of the detected utilities.
 62. The apparatus of claim 47, wherein the processor computes tolerance factor data associated with sensor data stored in memory.
 63. The apparatus of claim 47, wherein the processor weights the stored data using the tolerance factor data.
 64. The apparatus of claim 47, wherein the processor computes tolerance factor data associated with each of the detected utilities.
 65. The apparatus of claim 47, wherein the memory stores ground truth data and the processor processes the ground truth data to enhance accuracy of utility detection.
 66. The apparatus of claim 47, wherein the processor generates a map of the detected utilities using the sensor data.
 67. The apparatus of claim 66, wherein the processor incorporates data associated with the map within a Geographic Information System.
 68. The apparatus of claim 47, wherein the processor generates a 2-D map or a 3-D map of the detected utilities.
 69. The apparatus of claim 47, further comprising a display coupled to the processor, the processor causing the display to display data associated with one or more of the sensed physical parameters or one or more of the detected utilities. 